Benchmark Results for Combinatorial Game Complexity Across 674 Test Problems

Abstract

Despite sustained attention from the research community, combinatorial game complexity remains difficult to study outside well-funded laboratories. We assemble a dataset of 1616 observations and evaluate three competing models under matched conditions. Results show a 25% gain in accuracy alongside a marked reduction in variance between replicates. We discuss limitations and outline directions for follow-up work at the undergraduate level.